Prospective Validation of Computer-Assisted Detection of Early Lung Cancer in Chest X-Rays

Background: Computer-aided diagnosis (CAD) algorithms may be useful for the detection of pulmonary nodules, some of them early-stage primary lung cancers (LCs). Method: A CAD algorithm for the identification of pulmonary nodules in chest x-rays was used in a prospective cohort of patients without respiratory symptoms who underwent an x-ray. Chest x-rays were sorted according to the probability of the presence of a pulmonary nodule, and images placed in the highest percentiles by the algorithm were read by a radiologist, checked for previous diagnoses, and assessed for new primary LCs. Results: The radiological study confirmed the presence of a round opacities in 88 out of the 1842 chest x-rays placed in the highest percentiles (4.8%), 44 of which were found to be malignant (50%), and 7 of them undiagnosed primary LCs (7.9%). The CAD algorithm prompted a new diagnosis of primary LC in 0.4% of the sorted chest x-rays. Conclusion: A CAD algorithm prospectively identified chest x-rays with a high probability of pulmonary nodules among patients without respiratory symptoms. Radiologist-confirmed nodules were found in 4.8% of high-probability images, and previously undiagnosed primary lung cancers accounted for near 8% of confirmed round opacities and 1% of high-probability chest x-rays.